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A biomass dynamics modelling study to derive biological reference points and management requirements of 223 commercially important fish stocks in different maritime states of India was conducted. Two decades (1997–2016) of fishery-related data on the harvest of resources by different types of fishing fleets formed the input. The multigear nature of the fishery situation was solved by introducing a gear standardization parameter into the biomass dynamics model. The relative positions of the fish stocks were depicted through Kobe plots generated for the ten maritime states/union territory, and the fish stocks were categorized, based on the status, into sustainable, overfished, recovering, and overfishing. The results indicate that 34.1% of the assessed fish stocks in the country are sustainable, 36.3% are overfished, 26.5% are recovering, and 3.1% are in the overfishing status. Regionally, the percentage of sustainable fish stocks were high along the southwest coast (51.6%), overfished stocks were high along the northwest coast (54.2%), and recovering fish stocks were high along the northeast coast (47.8%). The national mean B/BMSY was estimated as 0.86, which is a strong reason for strengthening fisheries management. Fishing fleets harvesting overfished stocks were examined for each maritime state, and recommendations regarding reduction in annual fishing hours are made.

The marine fisheries sector in India supports livelihood of four million people and earn a significant amount of foreign exchange through export of marine fish and its products. Historic data showed that the total marine fish production in India maintains an overall upward trend with fluctuations. Periodic assessment of major fishery resource groups is necessary to manage the fishery for sustainability. Among different species groups, 50 commercially important resource groups accounting for about 97% of the national annual landings were individually studied by Markov Chain modeling of annual growth rates in landings. In addition, the time series data on landings of these marine fishery resource groups were analyzed randomness using 'runs test'. Limiting probabilities for all the nine defined states of each Markov Chain process were determined and status of the resources was derived based on limiting probabilities. Runs test on the time series sequences showed 19 of them having random behavior. It was found through Markov Chain modeling that 16 of the marine fishery resources have probability more than 0.8 to confine their annual growth rate between-0.25% and +0.25% providing high confidence regarding stable yield from harvest indicating stability of their stocks.

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Morphometric variables were measured to detect variation among the random population samples of Penaeus monodon from east and west coast-Kochi, Calicut, Mangalore, Karwar, Kakinada and Chennai of India. Among these variables, PCL showed the highest correlation with the tail weight (TLW) in both males (0.9605) and females (0.9639). Truss network analysis of 26 measurements from the six centres were log transformed and were subjected to Principal Component Analysis and accounted a total of 89.15% variations in truss measurements data and showed no separate cluster formation in the plot of sheared PC scores and hence confirm homogeneous stock structure.

Climate change is a global challenge today, with its impacts felt worldwide. The coastal regions around globe are more prone to the impacts of climate change than the inlands, fishing being one of the primary occupations of the coast, the fishermen community is the most vulnerable group to be affected by the climate change. Even with extensive scientific research in this arena there is a lacuna in finding a panacea to this existing problem. The objective of this study is to determine the scope of developing village level adaptation and mitigation plan for the community through a comprehensive analysis of the community perception on climate change impacts, vulnerability and existing adaptation mitigation strategies. In the chosen study villages of Ochanthuruth and Narakkal of Ernakulam district, the impact of climate change was felt on both resource and resource users based on a perception analysis made using comprehensive interview schedule administered across 300 households. The study revealed that the actual science and consequences of climate change impacts in a long run are not perceived well. The work suggests that concerted efforts in bringing about resilient community can be achieved through global understanding of the issue and coming up with area specific solutions with the inclusion of the much forgotten social factor-the stakeholders..